In computer vision, a class of algorithms generally known as Video Analytics has results that depend on the stability of the video signal. Video analytics can include human face tracking, a feature that is in high demand. Vibration, rotation and shaking affect the efficiency of video analytics algorithms. This is the case for face tracking and human tracking algorithms, many of which are based on an assumption about human face orientation. If the human face rotates too much, the detection and tracking will fail easily.
In a handheld device, rotation of the human face is typically corrected by a human hand stabilizing the camera. However, in a drone or a flying camera, vibration and rotation of the drone/camera during flight can make human face tracking difficult. A gimbal can help solve the problem, but the size and the cost of the gimbal make it very hard to adopt in low cost, low power consumer drone markets.
It would be desirable to implement electronic image stabilization to improve video analytics accuracy.